*4.1.1 Unit root test*

The VECM estimation is started by testing the data stationarity of each variable as the initial process. To detect the stationarity of each variable, the ADF test is used with the intercept model. Data sets are declared stationary if the average values and variants of the time series data do not change systematically over time or the averages and their variants are constant [29]. The ADF stationary test for each variable can be indicated as follows.

According to **Table 1**, at the level, there is no single variable that meets stationary requirements, either from FDR, NPF, or BOPO. It is indicated by the value of t-ADF which is greater than the Mackinnon critical value, so it is necessary to test at the first difference level shown in **Table 2**.

Based on **Table 2**, it can be concluded that all variables are stationary at the *first difference* with a predetermined critical value (α = 5%), as follows:


From the above tests, all variables have met data stationary. The ADF t-statistics are smaller than the McKinnon critical value 5% at the first difference level. Therefore, the next step is to estimate the data by VECM by selecting its lag length criteria.
